Accelerating Simulation & Analysis with Hybrid GPU Parallelization and Cloud Computing

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1 Accelerating Simulation & Analysis with Hybrid GPU Parallelization and Cloud Computing Innovation Intelligence Devin Jensen August 2012

2 Altair Knows HPC Altair is the only company that: makes HPC tools develops HPC applications and uses these to solve real HPC problems 500 Altair engineers worldwide use HPC every day for real-world modeling & simulation

3 Innovation Intelligence 26+ Years of Innovation 40+ Offices in 18 Countries Employees Worldwide

4 Customers Automotive Aerospace Heavy Equipment Government Life/Earth Sciences Consumer Goods Energy 3,200+ customers worldwide

5 Hardware Trends and Software Evolution Multi Level Parallelism Single Threaded & Vectorization SMP Parallelization MPI Clusterization Hybrid MPI/OpenMP & Heterogeneous CPU/GPU Source : Intel Corp. 5

6 Motivations to use GPU for Solvers $ Cost effective solution Power efficient solution G flops How much of the peak can we get? Which part of the code is best suited? How much coding effort is required? What will be the speedup for my application? Node Intel X Nodes Intel X Node+1 Nvidia 1 Node+2 Nvidia M2090 M2090 Gflop Peak (DP) Gflop cost in $ Gflops per Watt

7 NVIDIA Ecosystem based on CUDA (+ OpenACC with CRAY, PGI and CAPS) Any NVIDIA graphic card supports CUDA Strong market presence Products Tesla and Quadro GPUs based on the Fermi Architecture Announcement of Kepler Architecture, ~2X faster than Fermi, HyperQ, virtualization, 7

8 AcuSolve GPU Porting on NVIDIA CUDA High performance computational fluid dynamics software (CFD) The leading finite element based CFD technology High accuracy and scalability on massively parallel architectures S-duct 80K Degrees of Freedom Hybrid MPI/OpenMP for Multi-GPU test Xeon Nehalem CPU Nehalem CPU + Tesla GPU X* 3.3X* Lower is better 0 4 core CPU 1 core + 1 GPU 4 core CPU 2 core + 2 GPU *Performance gain versus 4 core CPU 8

9 RADIOSS Porting on GPU Assess the potential of GPU for RADIOSS Focus on Implicit Direct Solver Highly optimized compute intensive solver Limited scalability on multicores and cluster Iterative Solver Ability to solve huge problems with low memory requirement Efficient parallelization High cost on CPU due to large number of iterations for convergence Double Precision required Integrate GPU parallelization into our Hybrid parallelization technology 9

10 RADIOSS Porting on GPU & Accelerators CUDA official version planned for HW12 RADIOSS implicit direct solver and iterative solver available under Linux Support for NVIDIA Fermi and Kepler (K20 Q1 13) Altair RADIOSS presentation at GTC2012 OpenCL Beta version Only RADIOSS Implicit Iterative Solver available under Linux and Windows Support for AMD FirePro Altair RADIOSS presentation at AFDS

11 RADIOSS Direct Solver GPU Porting CUBLAS (DGEMM) perfect candidate to speed up update module Frontal matrix could be too huge to fit in GPU memory Frontal matrix could be too small and thus inefficient w/ GPU Data transfer is not trivial Only the lower triangular matrix is interesting Pivoting is required in real applications Pivot searching is a sequential operation Factor module has limited parallel potential It could be as expensive as update module in extreme case Asynchronous computing Overlap the computation Overlap the communication 11

12 RADIOSS Direct Solver Non Pivoting Case Linear static Non Pivoting Case Benchmark 2.8 Millions of Degrees of Freedom Platform Intel Xeon X5550, 4 Core, 48GB RAM NVIDIA C2070, CUDA 4.0 MKL 10.3, RHEL 5.1 GPU speedup - non-pivoting case solver elapsed 1,2 1 base(bcslib-ext) improved 1200 e l a p s e d ( s ) Lower is better p ro file (% ) 0,8 0,6 0, ,2 0 4 CPU 4 CPU + 1GPU 3.9X 2.9X 0 update total 12

13 RADIOSS Iterative Solver (Implicit) Preconditioned Conjugate Gradient (PCG) solves iteratively M -1. (Ax b) = 0 Convergence speed depends on preconditioner M Low memory consumption Efficient parallelization: SMP, MPI Porting under CUDA Few kernels to write in Cuda Sparse Matrix Vector Use of CUBLAS DAXPY & DDOT Extend Hybrid to multi GPUs programming MPI to manage communication between GPU Portions of code not GPU enabled benefit from OpenMP parallelization Programming model expandable to multi nodes with multiple GPUs 13

14 RADIOSS PCG Linear Benchmark #2 Linear Problem #2 Hood of a car with pressure loads Refined model Compute displacements and stresses Benchmark 2.2 Millions of Degrees of Freedom E la p s e d (s ) SMP 6-core Hybrid 2 MPI x 6 SMP SMP GPU Hybrid 2 MPI x 6 SMP + 2 Platform Performance 62 Millions of non zero Shells Solids RBE iterations NVIDIA PSG Cluster 2 nodes with: Dual NVIDIA M2090 GPUs CUDA v3.2 Intel Westmere 2x6 Linux RHEL 5.4 with Intel MPI 4.0 Elapsed time decreased by up to 13X E la p s e d (s ) X* 7.5X* 1 node - 2 Nividia M Hybrid 4 MPI x 6 SMP Hybrid 4 MPI x 6 SMP + 4 Lower is better Multi GPUs performance is better for bigger models X* 2 nodes - 4 Nvidia M2090 *Performance gain versus SMP 6-core 14

15 GPU For Explicit? Explicit is very difficult to port on GPU Data movement between CPU and GPU current bottleneck Require full memory allocated on GPU and therefore full code ported Huge development cost Challenge of multiple code bases Potential gain remains small with current technology approach Data locality and cache reuse is not possible on GPU Memory size limitation Follow hardware evolution AMD APU (CPU+GPU) Intel Xeon Phi NVIDIA through OpenACC initiative 15

16 Altair Solvers on NVIDIA GPUs RADIOSS implicit direct & iterative solvers have been successfully ported on NVIDIA GPU using CUDA Adding GPU improves performance of Altair solvers significantly For iterative solver, Hybrid MPP allows to run on multi GPU card workstation and GPU cluster with good scalability and enhanced performance GPU support for implicit solvers is planned for HyperWorks 12 16

17 HyperWorks 3D display OpenGL stereoscopic display in HyperMesh & HyperView Supported by NVIDIA graphics cards Compatible with NVIDIA 3D Vision glasses Available in HyperWorks 12.0

18 HyperView Performance Gains From Shaders Gains in graphics performance 2x to 6x improvement in animation frame rate, model rotation, & pan

19 Licensing Model for Solvers Licensing has been set to encourage GPU testing One GPU is considered as one additional core only 19

20 Where does PBS Professional manage NVIDIA GPUs? Tokyo Institute of Technology TSUBAME 2.0 Reliability Robust advance reservations GPU support Mixed architecture support (Linux, Windows) HP s biggest Top500 machine ~100,000 simultaneous jobs ~2,000 users PBS Professional offers THE best scalability in the industry NEC 2.4 Petaflops 17,984 cores 4,200 GPUs 80 TB mem 174 TB SSD 7 PB disk Decreed as one of the Greenest Decreed as one of the Greenest Production Supercomputer in the World on the June Production 2012 Green Supercomputer 500 List, for achieving in the World a high level on the of June energy-efficiency 2012 Green 500 List, for achieving a high level of energy-efficiency.

21 Purpose-Built for High Performance Computing IDC study (published 2009) on job scheduling ranked PBS Professional #1 Easy to Use Hard to Break Compute Manager Do More (with Less) Keep Track and Plan Open Architecture 5 Strategic Pillars

22 Accelerating Your Gateway to HPC Cloud Computing Structure our Thoughts High Performance [N/W& H/W] Dynamic Provisioning [Self Service] Multi-Tenant Large Data Handling Elasticity / Scale On Demand / Pay as you go Ease of access and use / Abstract

23 Accelerating your Gateway to HPC Cloud Computing End Users Needs Focus on My Task / Project Deliver Results! Does have Workstations Limited Access to Software Ideas, Innovation, Agility Does NOT have Expertise in IT Infrastructure Sufficient compute resources Financial / Abundance of Money

24 Accelerating your Gateway to HPC Cloud Computing End Users Needs Ease of Access: All you need is just a Browser to access HPC & Domain specific resources Ease of Use: All you need is a browser based application hiding the complexity Handle Big Data: All you need is a way to visualize the managed big data again through a browser based application User Interface Portals

25 Accelerating your Gateway to HPC Cloud Computing Altair Enterprise Portals Ease of Use Ease of Access Handle Big Data HyperWorks Enterprise Applications Compute Manager Display Manager Simulation Manager Process Manager Performance Manager

26 COMPUTE MANAGER Ease of Use Ease of Access Handle Big Data

27 Accelerating your Gateway to HPC Cloud Computing Compute Manager Let s See Ease of Use Ease of Access Handle Big Data

28 Accelerating your Gateway to HPC Cloud Computing Compute Manager Let s See Ease of Use Ease of Access Handle Big Data

29 Accelerating your Gateway to HPC Cloud Computing HyperWorks Enterprise Complete Simulation Lifecycle Management HyperWorks Units Compute Display Simulation Process Performance Manager Manager Manager Manager Manager HyperWorks Enterprise HyperWorks PBS Professional HyperWorks Units It is HyperWorks in the Cloud

30 Accelerating your Gateway to HPC Cloud Computing Implementation Models HyperWorks Enterprise PBS Works HyperWorks On-Demand Hybrid Cloud PBS Professional Private Cloud Public Cloud

31 HYPERWORKS ON-DEMAND A Public Cloud run by Altair

32 Accelerating your Gateway to HPC Cloud Computing HyperWorks On-Demand: The Basics IaaS State-of-the-art HPC (Infrastructure as a Service) computation nodes Scalable Provision up to 10,000 compute, cores QDR storage, Non-blocking networking InfiniBand and other basic computing Physical and cyber security resources where arbitrary software can be deployed and executed. Resource Provisioning PaaS Scheduling Security (Platform Framework as a Service) Licensing Framework To build and deploy consumer created applications using the infrastructure provided by Altair. Remote Visualization Framework Notification Framework Portal & Mash up Framework Collaboration Framework Powered by PBS Professional & HyperWorks Enterprise HyperWorks Solvers SaaS HyperWorks (Software as Desktop a Service) 1 Altair To Partner consume Alliance the 1 Altair provisioned application deployed on the cloud infrastructure from anywhere using any device through a thin client interface 1: coming a utility soonmode. IaaS + PaaS + SaaS = HWaaS

33 Accelerating your Gateway to HPC Cloud Computing The High-Powered Altair Data Center Scalable, modular facility located in Troy, MI Can be easily extended to support up to more than 10,000 cores Incorporates extensive physical and cyber security measures Extremely high compute-power density A state-of-the-art facility for HPC simulation computing

34 Accelerating your Gateway to HPC Cloud Computing HyperWorks On-Demand Altair s user portals is the gateway to HyperWorks On-Demand

35 Altair Knows HPC Altair is the only company that: makes HPC tools develops HPC applications and uses these to solve real HPC problems 500 Altair engineers worldwide use HPC every day for real-world modeling & simulation

36 For More Information Contact Us Devin Jensen Director, Americas PBS Field Operations Visit Us Online Thanks, NVIDIA Thank YOU!

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